Is it good to learn big data Hadoop? by Radhika K
Answer by Radhika K:
Still confused whether or not to learn Big data? Let us see reasons you should start learning this trending technology now:
Why Big Data ?
Let’s start with what industry leaders say about Big Data:
- Gartner – Big Data is the new Oil
- IDC – Big Data market will be growing 7 times faster than the overall IT market
- IBM – Big data is not just a technology – it’s a Business Strategy for capitalizing on information resources
- IBM – Big Data is a biggest buzz word because technology makes it possible to analyze all available data
- McKinsey – There will be shortage of 1500000 Big Data professionals by the end of 2018
Industries today are searching new and better ways to maintain their position and be prepared for the future. According to experts, Big Data analytics provides leaders a path to capture insights and ideas to stay ahead in the tough competition.
What is Big Data ?
So, What is Big data? Different publishers have given their own definition for Big data to explain this buzzword.
According to Gartner:
Big data is huge-volume, fast-velocity and different-variety information assets that demand innovative platform for enhanced insights and decision making.
A Revolution, authors explain it as:
Big Data is a way to solve all the unsolved problems related to data management and handling, earlier industry were used to live with such problems. With Big data analytics you can unlock hidden patterns and know 360 degree view of customers and better understand their needs.
Demystify Big Data
In other words, big data gets generated in multiterabyte quantities, changes fast and comes in varieties of forms that is difficult to manage and process using RDBMS or other traditional technologies. Big Data solutions provide the tools, methodologies and technologies that are used to capture, store, search & analyze the data in seconds to find relationships and insights for innovation and competitive gain that were previously unavailable.
80% of the data getting generated today is unstructured and cannot be handled by our traditional technologies. Earlier, amount of data generated was not that high and we were keep archiving the data as there was just need of historical analysis of data. But today data generation is in petabytes that it is not possible to archive the data again and again and retrieve it again when needed as data scientists need to play with data now and then for predictive analysis unlike historical as used to be done with traditional.
Big Data Use-cases
Below are some of the Big data use cases from different domains:
- Netflix Uses Big Data to Improve Customer Experience
- Promotion and campaign analysis by Sears Holding
- Sentiment analysis
- Customer Churn analysis
- Predictive analysis
- Real time ad matching and serving